Assemble prerequisites

We used Caffe to train the models, and computed necessary statistics including pair-wise unit correlations, unit activation mean, pair-wise unit mutual information etc. In this demo, to minimize the effort for you to try out the fun experiments, we have provided a link for you to download all the necessities (pre-trained models, unit statistics, unit visualizations, pre-trained sparse prediction models).

To run through the demo, you only need the standard packages of IPython, numpy, networkx, sklearn and matplotlib packages. Depending on your setup, it may be possible to install these via pip install ipython numpy matplotlib networkx sklearn.

Run experiments with pre-computed statistics

Once the data folder is downloaded, the results can be reproduced using the included IPython notebook experiments/convergent_learning_notebook.ipynb.
Start the IPython Notebook server:

$ cd experiments
$ ipython notebook

Select the convergent_learning_notebook.ipynb notebook and execute the included
code.